Got a chance this morning to read today's Wall Street Journal cover to cover (3 hour plane flight with accidentally dead PC battery) and ran across an article discussing how skyrocketing energy costs are starting to impact manufacturers. The gist of the article is as higher energy costs translate in higher transport costs rise, some of basic assumptions used to build manufacturing strategies over the past couple of decades are starting to unravel. The availability of cheap transport is fundamental to two of the biggest trends in manufacturing: just in time and offshore. It seems that when it starts to cost twice as much to ship parts and products across the world that some manufacturers are starting to rethink how and where things get made.

As I was reading, I started to think about ways that PLM might be able to help with this problem. A few of the ideas that I came up with:

Make lighter weight components. This saves both transport and operating costs if the product is mobile.

Copy factory setups from one location to another. One of the big arguments to getting one big factory setup is that you learn faster and can share hose learnings with all lines. The digital factory aspects of PLM can make this effect work across a distributed set of smaller factories that are optimized for getting the heavier items closer to the end user.

Componentize design to allow for manufacturing of 'expensive to transport' components closest to destination. Sort of the same as the second point, but this is more focused on product rather than process design.

Interested to hear what other ideas are out there about how PLM can help deal with >140 bbl oil. Drop me any ideas in comments.

Another option would be to look at simulation of delivery and transporation strategies.

The Tecnomatix Plant Simulation product is part of our PLM solution set and with it we have the ability to simulate the transportation and delivery of products/goods. This aspect of the product is not often looked at because most everyone is focused on what is happening within the factory itself and what is going on at the shop floor. But the transportation of a product from one location to another is all a part of its overall lifecycle and should be taken into consideration during manufacturing process planning.

We have a few organizations that have done simulations on delivery and transportation strategies – some examples include…

...a major German automobile manufacturer and the simulation of truck deliveries to their Munich plant. The original objective of the project was to reduce the number of trucks inside the plant facility and improve traffic flow. While they successfully reduced the number of trucks by 10% and reduced the time the trucks spent inside the facility by 12.5%—they also found that fuel consumption was improved due to the drivers spending less time idling in the waiting areas.

...one of the largest food companies in Russia did a much larger scale simulation of deliveries throughout Russia and Eastern Europe. This might actually be a better example of how Plant Simulation could help to optimize delivery and transportation strategies on a more global scale. The objective was to optimize the transporation of some 200 different product variants within a distribution network that included 15 warehousing facilities. In the end this particular food company was able to reduce the number of trucks for daily deliveries by 7 and they reduced the total transportation time by 5-hours. This translated into a 10.6% reduction in delivery costs per day.

Not everyone will have the ability to build new plants closer to where they need product, or break-up larger plants and re-distribute them into smaller plants closer to where product is needed. The capital expenditure to build and/or relocate a plant is extremely high. It still might be necessary to do something at the plant level at some point, but as an interim I wouldn’t be surprised if there isn’t some squeezing and optimizing that could be done at the delivery and transportation level, which could help to offset some of the rising fuel costs.

Chris Kelley’s analysis that the rising cost of fuel will change the economics of both manufacturing products in low-wage countries and just-in-time deliveries is accurate. And a couple of his suggestions for coping with these trends also are good. What’s not obvious is that just saying “PLM” will enable customers to follow his suggestions. Let’s consider them one by one:

“Make lighter weight components.” When used properly, analytical software can help reduce unnecessary materials while maintaining strength and rigidity. However, if lighter products break more often, they are no bargain. Analytical software must be used intelligently and in coordination with physical testing to optimize weight while retaining quality.

“Copy factory setups from one location to another.” Unfortunately, few companies have the same factories replicated all around the world. (Intel is a notable exception.) So just copying factory setups won’t work. It might make sense to copy factory processes if they can be easily modified to suit each plant. But sometimes it is easier to start over than to modify somebody else’s computer model.

“Make fixed cost lower component of overall factory cost.” I don’t see what PLM can do to lower fixed costs. More intelligent design can make factories cheaper to build, but anybody who has ever built a plant will know that few companies have the luxury of thoughtful planning in the design stage.

“Componentize design to allow for manufacturing of ‘expensive to transport’ components closest to destination.” I’m not sure what this statement means.

Jeff Miller’s suggestion that companies spend more on tools to help simulate and optimize their distribution systems is a good one. In general, senior executives at manufacturing companies should recognize that in an age of higher fuel and material costs, good engineering and planning reduce costs. And engineers need good software to enable them to work quickly and efficiently.

Steve - thanks for the comment. Couldn’t agree more on your first point: you have to use analytical tools intelligently. What’s more you have to use them to answer the right questions. If you setup an optimization to minimize weight without considering a minimum required level of strength or durability you haven’t done your customers any favors.

Relative to copying factory setups, that’s what I meant originally: not necessarily copying the machine to machine layout, but rather the overall process. Again agree that if the assets in one factory are wildly different from those in another factory then this may produce minimal returns, but I think that is less likely if the same product is being manufactured at both factories

On the third point, I don’t think that not having the time to do planning is a good enough excuse. If there is real value here (and of course, I think there is) then companies will make time. I think its the same sort of cultural change that had to take place 25 years ago with mechanical design. At first it was seen as an ‘extra step’ that you did before you got to the ‘real work’ of producing your drawings. Slowly designers began to realize that doing design digitally actually was a great time saver. It is the same with digital factory design - plant engineers are starting to realize a little planning and simulation in the digital domain is time well spent up front before concrete gets poured or machines get moved.

My last point was intended to highlight the fact that by using design tools to break apart a product into subsystems based on transport costs and then select locations to manufacture those subsystems (internal or suppliers) based on proximity to final assembly, transport costs can be minimized. Basically, if you have a choice of two suppliers for your heaviest components with similar quality and price, pick the one that’s closest to you.